共查询到19条相似文献,搜索用时 187 毫秒
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当前炼油企业氢气需求持续增长,导致炼厂成本及生产过程温室气体排放增加,炼油企业通过增设轻烃回收单元对氢气和轻烃组分进行回收利用,能有效缓解这一现状。因此,在氢气网络优化中有必要考虑轻烃回收单元。本研究提出了一种集成轻烃回收单元的氢气网络多目标数学规划模型,对轻烃回收单元采用代理模型建模方法,解决了直接嵌入严格机理模型可能导致的高计算成本问题,以总年度费用最小为优化目标,同时将系统的环境影响也纳入优化目标。实例计算表明,所提出的方法能够有效降低氢气网络的年度费用及温室气体排放,并揭示了集成轻烃回收单元的氢气网络经济性能与环境影响之间的权衡关系,为工业应用提供了一定的理论基础。 相似文献
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通过反应系统综合优化获得经济效益好、对环境友好的反应系统是大多化工厂提高全流程整体经济和环境性能的重要手段。反应器网络综合优化方法主要包括可得区法、导数分析法、超结构优化法、目标类法、经验推断法和分布参数法等,然而却很少有文献报道对反应器网络进行多目标综合优化。由于过程中往往存在多个相互冲突的目标函数,所以仅仅依靠单目标对反应器网络进行综合优化已显得不合适。本文采用分布参数法建立多目标优化模型,目标函数为经济最大化和环境影响最小,并采用非支配排序基因算法(NSGA-Ⅱ)进行优化得到Pareto最优解集。 相似文献
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针对生态工业园区中碳-氢-氧共生网络,基于多尺度原子标定方法,同时考虑经济和环境因素及回用副产碳氢氧化合物,本工作提出了一种多目标优化及决策的方法,从备选方案中获得最优方案。该方法采用数学规划法,分别以最小总年度成本和二氧化碳年度排放量为目标函数进行全局优化,建立了混合整数非线性规划模型;采用ε-约束法,将二氧化碳年度排放量转化为约束条件,得到了总年度成本与二氧化碳年度排放量帕累托前沿,发现总年度成本与二氧化碳排放量成反比;采用多维偏好分析的线性规划和逼近于理想解的排序决策方法对帕累托前沿进行最优决策,发现两者选择同一点作为最优决策。基于所提出的方法对某工业园区进行优化,结果表明,合理利用现有副产碳氢氧化合物,可以减少原材料成本,从而使总年度成本和二氧化碳年度排放量分别减少了63.44%和76.99%。 相似文献
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生物燃料作为一种可部分代替化石燃料的潜在能源具有绿色、可再生、无硫等优势,但其生产成本一般较高。生物质油与蜡油在催化裂化装置中的共炼通过利用炼厂已有设备可有效降低生物炼厂的投资费用进而降低生物燃料的生产成本。为同时降低共炼过程的经济费用和环境影响以筛选最优的生物质原料和生物质油制备技术,采用Eco-indicator 99方法量化共炼过程的环境影响,提出了针对该过程的多目标优化模型。结果表明:无论是降低经济费用还是减少环境影响,采用催化热解技术制备生物质油优于快速热解;不同目标下所获得的最优生物质原料不同;生物质原料在费用和环境影响中占比最大。因此,在对共炼过程进行优化时,需要考虑过程对环境的影响,而降低生物质原料的消耗对共炼过程费用和环境影响的降低最为有效。 相似文献
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针对跨临界CO2热泵成本过高与占用空间大等问题,提出了一种基于经济性与实用性的数据驱动跨临界CO2热泵多目标优化设计方法。本文通过对跨临界CO2热泵进行性能模拟获得大量的驱动数据,然后经由BP神经网络构建跨临界CO2热泵的热力学预测模型,并且从投资、运营、环境以及空间占用等多角度建立跨临界CO2热泵的多目标优化模型。最后以住宅用户最关心的总年度成本与水箱容积为设计优化目标,通过精英策略非支配排序遗传算法(NSGA-Ⅱ)与TOPSIS决策法进行最优设计方案求解。案例研究表明,占用空间小、总年度成本低的最优设计方案的水箱体积为0.235m3、总年度成本为958.1USD/a。且通过分析设计参数对优化目标的影响,发现水箱保温层厚度的影响主要集中在一个较优区域,水箱直径与高度的影响较大,而气冷器换热温差的影响较小。 相似文献
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ZW多产品间歇过程调度及在线调整 总被引:1,自引:1,他引:1
针对多产品间歇过程调度提出了分层递阶的Petri网建模方法,利用赋时Petri和Petri网的简化技术描述不同层次的生产问题,具有很强的模型描述能力。另外,在调度决策层可以方便地集成优化策略和在线调整算法,使问题求解更加灵活。 相似文献
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In this contribution we present an online scheduling algorithm for a real world multiproduct batch plant. The overall mixed integer nonlinear programming (MINLP) problem is hierarchically structured into a mixed integer linear programming (MILP) problem first and then a reduced dimensional MINLP problem, which are optimized by mathematical programming (MP) and genetic algorithm (GA) respectively. The basis idea relies on combining MP with GA to exploit their complementary capacity. The key features of the hierarchical model are explained and illustrated with some real world cases from the multiproduct batch plants. 相似文献
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We address the bi-criterion optimization of batch scheduling problems with economic and environmental concerns. The economic objective is expressed in terms of productivity, which is the profit rate with respect to the makespan. The environmental objective is evaluated by means of environmental impact per functional unit based on the life cycle assessment methodology. The bi-criterion optimization model is solved with the ε-constraint method. Each instance is formulated as a mixed-integer linear fractional program (MILFP), which is a special class of non-convex mixed-integer nonlinear programs. In order to globally optimize the resulting MILFPs effectively, we employ the tailored reformulation-linearization method and Dinkelbach's algorithm. The optimal solutions lead to a Pareto frontier that reveals the tradeoff between productivity and environmental impact per functional unit. To illustrate the application, we present two case studies on the short-term scheduling of multiproduct and multipurpose batch plants. 相似文献
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Elisabet Capón‐García Aarón D. Bojarski Antonio Espuña Luis Puigjaner 《American Institute of Chemical Engineers》2013,59(2):429-444
The simultaneous consideration of economic and environmental objectives in batch production scheduling is today a subject of major concern. However, it constitutes a complex problem whose solution necessarily entails production trade‐offs. Unfortunately, a rigorous multiobjective optimization approach to solve this kind of problem often implies high computational effort and time, which seriously undermine its applicability to day‐to‐day operation in industrial practice. Hence, this work presents a hybrid optimization strategy based on rigorous local search and genetic algorithm to efficiently deal with industrial scale batch scheduling problems. Thus, a deeper insight into the combined environmental and economic issues when considering the trade‐offs of adopting a particular schedule is provided. The proposed methodology is applied to a case study concerning a multiproduct acrylic fiber production plant, where product changeovers influence the problem results. The proposed strategy stands for a marked improvement in effectively incorporating multiobjective optimization in short‐term plant operation. © 2012 American Institute of Chemical Engineers AIChE J, 59: 429–444, 2013 相似文献
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The current manufacturing environment for process industry has changed from a traditional single-site, single market to a more integrated global production mode where multiple sites are serving a global market. In this paper, the integrated planning and scheduling problem for the multisite, multiproduct batch plants is considered. The major challenge for addressing this problem is that the corresponding optimization problem becomes computationally intractable as the number of production sites, markets, and products increases in the supply chain network. To effectively deal with the increasing complexity, the block angular structure of the constraints matrix is exploited by relaxing the inventory constraints between adjoining time periods using the augmented Lagrangian decomposition method. To resolve the issues of non-separable cross-product terms in the augmented Lagrangian function, we apply diagonal approximation method. Several examples have been studied to demonstrate that the proposed approach yields significant computational savings compared to the full-scale integrated model. 相似文献
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A novel adaptive surrogate modeling‐based algorithm for simultaneous optimization of sequential batch process scheduling and dynamic operations
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A novel adaptive surrogate modeling‐based algorithm is proposed to solve the integrated scheduling and dynamic optimization problem for sequential batch processes. The integrated optimization problem is formulated as a large scale mixed‐integer nonlinear programming (MINLP) problem. To overcome the computational challenge of solving the integrated MINLP problem, an efficient solution algorithm based on the bilevel structure of the integrated problem is proposed. Because processing times and costs of each batch are the only linking variables between the scheduling and dynamic optimization problems, surrogate models based on piece‐wise linear functions are built for the dynamic optimization problems of each batch. These surrogate models are then updated adaptively, either by adding a new sampling point based on the solution of the previous iteration, or by doubling the upper bound of total processing time for the current surrogate model. The performance of the proposed method is demonstrated through the optimization of a multiproduct sequential batch process with seven units and up to five tasks. The results show that the proposed algorithm leads to a 31% higher profit than the sequential method. The proposed method also outperforms the full space simultaneous method by reducing the computational time by more than four orders of magnitude and returning a 9.59% higher profit. © 2015 American Institute of Chemical Engineers AIChE J, 61: 4191–4209, 2015 相似文献
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Elisabet Capón‐García Aarón D. Bojarski Antonio Espuña Luis Puigjaner 《American Institute of Chemical Engineers》2011,57(10):2766-2782
In batch process scheduling, production trade‐offs arise from the simultaneous consideration of different objectives. Economic goals are expressed in terms of plant profitability and productivity, whereas the environmental objectives are evaluated by means of metrics originated from the use of life cycle assessment methodology. This work illustrates a novel approach for decision making by using multiobjective optimization. In addition, different metrics are proposed to select a possible compromise based on the distance to a nonexistent utopian solution, whose objective function values are all optimal. Thus, this work provides a deeper insight into the influence of the metrics selection for both environmental and economic issues while considering the trade‐offs of adopting a particular schedule. The use of this approach is illustrated through its application to a case study related to a multiproduct acrylic fiber production plant, special attention is put to the influence of product changeovers. © 2010 American Institute of Chemical Engineers AIChE J, 57: 2766–2782, 2010 相似文献
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In this contribution, a novel linear generalized disjunctive programming (LGDP) model is developed for the design of multiproduct batch plants optimizing both process variables and the structure of the plant through the use of process performance models. These models describe unit operations using explicit expressions for the size and time factors as functions of the process variables with the highest impact. To attain a linear formulation, values of the process variables as well as unit sizes are selected from a set of meaningful discrete values provided by the designer. Regarding structural alternatives, both kinds of unit duplications in series and in parallel are considered in this approach. The inclusion of the duplication in series requires different detailed models that depend on the structure selected. Thus, in a new approach for the multiproduct batch plant design, a set of potential structural alternatives for the plant is defined. © 2010 American Institute of Chemical Engineers AIChE J, 2011 相似文献